Publications

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2019
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Aerts, P., Dirckx, J. J. J., and Sijbers, J., A low-cost and easy-to-use phantom for cone-beam geometry calibration of a tomographic X-ray system, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.PDF icon Download paper (1.93 MB)
T. Elberfeld, Bazrafkan, S., De Beenhouwer, J., and Sijbers, J., Mixed-Scale Dense Convolutional Neural Network based Improvement of Glass Fiber-reinforced Composite CT Images, 4th International Conference on Tomography of Materials & Structures. 2019.
N. Six, De Beenhouwer, J., and Sijbers, J., poly-DART: A discrete algebraic reconstruction technique for polychromatic X-ray CT, Optics Express, vol. 27, no. 23, pp. 33427-33435, 2019.PDF icon Download paper (997.08 KB)
B. Auer, De Beenhouwer, J., Zeraatkar, N., Kuo, P. H., Furenlid, L. R., and King, M. A., Preliminary investigation of attenuation and scatter correction strategies for a next-generation SPECT system dedicated to quantitative clinical brain imaging, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Manchester, UK, 2019.
A. Könik, Auer, B., De Beenhouwer, J., Kalluri, K., Zeraatkar, N., Furenlid, L. R., and King, M. A., Primary, scatter, and penetration characterizations of parallel-hole and pinhole collimators for I-123 SPECT, Physics in Medicine & Biology, vol. 64, no. 24, p. 245001, 2019.PDF icon i123_spectra_final_revision_11_7_19.pdf (7.63 MB)
J. Sanctorum, De Beenhouwer, J., Weissenböck, J., Heinzl, C., Kastner, J., and Sijbers, J., Simulated grating-based x-ray phase contrast images of CFRP-like objects, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019, pp. 1-8.PDF icon Download paper (706.73 KB)
B. Fröhler, Melo, Lda Cunha, Weissenböck, J., Kastner, J., Möller, T., Hege, H. - C., Gröller, E., Sanctorum, J., De Beenhouwer, J., Sijbers, J., and Heinzl, C., Tools for the Analysis of Datasets from X-Ray Computed Tomography based on Talbot-Lau Grating Interferometry, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.PDF icon Download paper (1.07 MB)
Y. - T. Ling, Cools, S., De Beenhouwer, J., Sijbers, J., and Vandervorst, W., A Trajectory Based Bottom-Up Volume Reconstruction Method for Atom Probe Tomography, European Atom Probe Workshop. 2019.
B. Fröhler, Elberfeld, T., Möller, T., Weissenböck, J., De Beenhouwer, J., Sijbers, J., Hege, H. - C., Kastner, J., and Heinzl, C., A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science, Computer Graphics Forum, vol. 38, no. 3, pp. 273-283, 2019.
2020
P. Paramonov, Lumbeeck, L. - P., De Beenhouwer, J., and Sijbers, J., Accurate terahertz simulation with ray tracing incorporating beam shape and refraction, in IEEE ICIP , 2020.PDF icon Download paper (190.62 KB)
D. Frenkel, De Beenhouwer, J., and Sijbers, J., An adaptive probability map for the Discrete Algebraic Reconstruction Technique, 10th Conference on Industrial Computed Tomography (ICT 2020). 2020.
J. Renders, Sijbers, J., and De Beenhouwer, J., Adjoint pairs of image warping operators for motion modeling in 4D-CT, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020.PDF icon Download paper (617.11 KB)
B. Fröhler, Elberfeld, T., Möller, T., Hege, H. - C., De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., Analysis and Comparison of Algorithms for the Tomographic Reconstruction of Curved Fibers, in 10th Conference on Industrial Computed Tomography (ICT 2020), 2020.PDF icon Download paper (703.79 KB)
B. Fröhler, Elberfeld, T., Möller, T., Hege, H. - C., De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., Analysis and Comparison of Algorithms for the Tomographic Reconstruction of Curved Fibres, Nondestructive Testing and Evaluation, vol. 35, no. 3, pp. 328-341, 2020.
B. Auer, Kalluri, K., Abayazeed, A. H., De Beenhouwer, J., Zeraatkar, N., Lindsay, C., Momsen, N., R. Richards, G., May, M., Kupinski, M. A., Kuo, P. H., Furenlid, L. R., and King, M. A., Aperture size selection for improved brain tumor detection and quantification in multi-pinhole 123I-CLINDE SPECT imaging, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Boston, USA (2020), 2020.
V. Nguyen, De Beenhouwer, J., Bazrafkan, S., Hoang, A. - T., Van Wassenbergh, S., and Sijbers, J., BeadNet: a network for automated spherical marker detection in radiographs for geometry calibration, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020, pp. 518-521.PDF icon Download paper (2.16 MB)
M. Ljubenović, Bazrafkan, S., De Beenhouwer, J., and Sijbers, J., CNN-based Deblurring of Terahertz Images, in Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP), 2020, vol. 4, pp. 323-330.PDF icon Download paper (16.31 MB)
A. Presenti, Bazrafkan, S., Sijbers, J., and De Beenhouwer, J., Deep learning-based 2D-3D sample pose estimation for X-ray 3DCT, in 10th Conference on Industrial Computed Tomography (ICT 2020), 2020.
L. F. Alves Pereira, De Beenhouwer, J., Kastner, J., and Sijbers, J., Extreme Sparse X-ray Computed Laminography Via Convolutional Neural Networks, in ICTAI 2020, 2020.PDF icon Download paper (2.5 MB)
B. Auer, Kalluri, K., De Beenhouwer, J., Zeraatkar, N., Momsen, N., Kuo, P. H., Furenlid, L. R., and King, M. A., Keel-Edge Height Selection for Improved Multi-Pinhole 123I Brain SPECT Imaging, Journal of Nuclear Medicine, vol. 61, p. 573, 2020.PDF icon Download paper (127.73 KB)
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Bazrafkan, S., Dirckx, J. J. J., and Sijbers, J., A low-cost geometry calibration procedure for a modular cone-beam X-ray CT system, Nondestructive Testing and Evaluation , vol. 35, no. 3, pp. 252-265, 2020.
B. G. Booth, Sijbers, J., and De Beenhouwer, J., A Machine Learning Approach to Growth Direction Finding for Automated Planting of Bulbous Plants, Scientific Reports, vol. 10, no. 661, 2020.
T. Van De Looverbosch, Bhuiyan, H. Rahman, Verboven, P., Dierick, M., Van Loo, D., De Beenhouwer, J., Sijbers, J., and Nicolai, B., Nondestructive internal quality inspection of pear fruit by X-ray CT using machine learning, Food Control, vol. 113, no. 107170, pp. 1-13, 2020.
L. - P. Lumbeeck, Paramonov, P., Sijbers, J., and De Beenhouwer, J., The Radon Transform for Terahertz Computed Tomography Incorporating the Beam Shape, in IEEE ICIP, 2020.PDF icon Download paper (692.64 KB)
B. Auer, Kalluri, K., De Beenhouwer, J., Doty, K., Zeraatkar, N., Kuo, P. H., Furenlid, L. R., and King, M. A., Reconstruction using Depth of Interaction Information of Curved and Flat Detector Designs for Quantitative Multi-Pinhole Brain SPECT, Journal of Nuclear Medicine, vol. 61, p. 103, 2020.PDF icon snm2020_recon_curved.pdf (103.23 KB)

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